Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "182"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 182 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 32 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 32 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 182, Node N13:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2460015 digital_ok 100.00% 0.00% 100.00% 0.00% - - -0.176406 14.554369 -0.461803 11.357707 -0.456454 7.017774 5.551098 2.570690 0.6087 0.0515 0.4621 nan nan
2460014 digital_ok 100.00% 0.00% 100.00% 0.00% - - -0.123552 12.338161 -0.595288 8.536244 -0.825179 10.480895 11.599716 1.463141 0.5882 0.0438 0.4601 nan nan
2460013 digital_ok 100.00% 0.00% 100.00% 0.00% - - -0.088318 14.583523 -0.402167 11.341005 -0.649579 7.086205 8.744673 3.176138 0.6044 0.0469 0.4663 nan nan
2460012 digital_ok 100.00% 0.00% 100.00% 0.00% - - -0.145023 13.698909 -0.489099 11.128421 -0.714162 7.776294 8.352995 4.287897 0.6005 0.0502 0.4522 nan nan
2460011 digital_ok 100.00% 0.00% 100.00% 0.00% - - -0.109760 14.756647 0.237551 14.894403 6.550481 16.101765 6.719311 2.823063 0.6232 0.0531 0.4642 nan nan
2460010 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.030122 16.094191 0.792119 12.333323 -0.773136 10.520258 -0.628582 2.703597 0.6360 0.0534 0.4737 nan nan
2460009 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.116448 14.883629 0.505386 13.596881 -0.719313 8.869103 -0.225146 2.716631 0.6361 0.0542 0.4773 nan nan
2460008 digital_ok 100.00% 0.00% 100.00% 0.00% - - -0.000568 18.234719 0.547089 14.953364 1.866638 7.788855 -0.218604 5.640240 0.6711 0.0572 0.4689 nan nan
2460007 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.052333 13.607097 -0.953733 11.687916 -0.379283 7.247762 6.169762 2.937926 0.6434 0.0522 0.4679 nan nan
2459999 digital_ok 0.00% 98.41% 98.91% 0.00% - - nan nan nan nan nan nan nan nan 0.3312 0.3248 0.2650 nan nan
2459998 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.050719 11.469928 -0.823364 9.881916 -0.377191 10.301299 10.201294 2.470228 0.6261 0.0453 0.4820 nan nan
2459997 digital_ok 100.00% 0.00% 100.00% 0.00% - - -0.071774 12.525558 -0.573272 10.629936 -0.537573 9.645299 11.960757 3.784031 0.6350 0.0507 0.4975 nan nan
2459996 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.191453 13.534459 0.473986 13.031173 5.912832 9.308372 0.655310 1.447257 0.6471 0.0506 0.4929 nan nan
2459995 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.173471 13.680941 -0.670386 12.222810 8.981446 9.569925 2.586985 1.366704 0.6353 0.0547 0.4772 nan nan
2459994 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.157897 13.259359 -1.166283 10.703074 -0.001583 9.611869 3.588806 2.565900 0.6285 0.0471 0.4753 nan nan
2459993 digital_ok 100.00% 0.00% 98.92% 0.00% - - 0.060669 12.471974 -1.016151 9.909228 -0.138953 10.992488 2.884272 2.315954 0.6132 0.0410 0.4650 nan nan
2459991 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.230627 15.443711 -1.155353 10.489422 0.989484 10.820878 4.077660 0.915330 0.6412 0.0452 0.4966 nan nan
2459990 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.153064 12.706613 -1.281780 10.183682 -0.062419 11.048026 5.246792 1.165562 0.6379 0.0485 0.4866 nan nan
2459989 digital_ok 100.00% 97.30% 97.51% 0.00% - - 245.978957 246.527131 inf inf 2963.635450 2954.900643 4761.498448 4772.964562 0.5080 0.4437 0.3070 nan nan
2459988 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.345567 15.088415 -1.360423 10.465418 -0.700934 13.261314 3.857661 0.722414 0.6335 0.0439 0.4857 nan nan
2459987 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.169927 12.638774 -1.381799 10.345162 15.496596 8.017265 4.431810 2.594379 0.6407 0.0486 0.4924 nan nan
2459986 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.483274 15.499530 -1.105219 11.158024 3.626443 11.316802 2.595480 9.886906 0.6581 0.0465 0.4790 nan nan
2459985 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.434438 14.017117 -0.872422 10.400560 11.584559 8.657785 10.414465 2.287985 0.6418 0.0469 0.4946 nan nan
2459984 digital_ok 100.00% 0.00% 98.32% 0.00% - - 0.250117 13.486348 0.263684 10.784678 3.021609 12.121424 -0.904084 3.598452 0.6559 0.0551 0.4914 nan nan
2459983 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.152347 13.174448 0.093819 10.188555 3.348273 11.211746 0.335167 6.314968 0.6674 0.0504 0.4806 nan nan
2459982 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.134890 10.510283 -0.629934 8.697161 0.182323 5.315459 0.339387 3.238989 0.7146 0.0470 0.5011 nan nan
2459981 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.287902 12.106894 -1.153003 10.829090 0.229163 12.422410 7.402290 1.130681 0.6411 0.0482 0.4902 nan nan
2459980 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.029169 11.695642 -1.155232 9.907259 0.255774 10.848173 0.000658 5.352528 0.6817 0.0488 0.4950 nan nan
2459979 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.131346 12.170079 -1.154140 9.257439 -0.326416 10.156395 6.903089 0.769786 0.6336 0.0441 0.4871 nan nan
2459978 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.199564 12.369913 -1.197971 9.966466 -0.050003 11.023486 10.338439 1.523037 0.6341 0.0423 0.4946 nan nan
2459977 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.284804 13.125412 -1.109285 9.832856 0.085019 11.364589 6.427282 1.335939 0.6006 0.0495 0.4545 nan nan
2459976 digital_ok 100.00% 0.00% 100.00% 0.00% - - 0.294096 12.606954 -1.147543 10.234781 -0.578666 10.918255 7.012695 1.303232 0.6403 0.0439 0.4926 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 182: 2460015

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 14.554369 14.554369 -0.176406 11.357707 -0.461803 7.017774 -0.456454 2.570690 5.551098

Antenna 182: 2460014

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 12.338161 -0.123552 12.338161 -0.595288 8.536244 -0.825179 10.480895 11.599716 1.463141

Antenna 182: 2460013

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 14.583523 -0.088318 14.583523 -0.402167 11.341005 -0.649579 7.086205 8.744673 3.176138

Antenna 182: 2460012

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 13.698909 -0.145023 13.698909 -0.489099 11.128421 -0.714162 7.776294 8.352995 4.287897

Antenna 182: 2460011

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Temporal Variability 16.101765 -0.109760 14.756647 0.237551 14.894403 6.550481 16.101765 6.719311 2.823063

Antenna 182: 2460010

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 16.094191 0.030122 16.094191 0.792119 12.333323 -0.773136 10.520258 -0.628582 2.703597

Antenna 182: 2460009

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 14.883629 0.116448 14.883629 0.505386 13.596881 -0.719313 8.869103 -0.225146 2.716631

Antenna 182: 2460008

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 18.234719 18.234719 -0.000568 14.953364 0.547089 7.788855 1.866638 5.640240 -0.218604

Antenna 182: 2460007

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 13.607097 0.052333 13.607097 -0.953733 11.687916 -0.379283 7.247762 6.169762 2.937926

Antenna 182: 2459999

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 182: 2459998

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 11.469928 0.050719 11.469928 -0.823364 9.881916 -0.377191 10.301299 10.201294 2.470228

Antenna 182: 2459997

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 12.525558 -0.071774 12.525558 -0.573272 10.629936 -0.537573 9.645299 11.960757 3.784031

Antenna 182: 2459996

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 13.534459 0.191453 13.534459 0.473986 13.031173 5.912832 9.308372 0.655310 1.447257

Antenna 182: 2459995

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 13.680941 0.173471 13.680941 -0.670386 12.222810 8.981446 9.569925 2.586985 1.366704

Antenna 182: 2459994

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 13.259359 0.157897 13.259359 -1.166283 10.703074 -0.001583 9.611869 3.588806 2.565900

Antenna 182: 2459993

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 12.471974 0.060669 12.471974 -1.016151 9.909228 -0.138953 10.992488 2.884272 2.315954

Antenna 182: 2459991

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 15.443711 0.230627 15.443711 -1.155353 10.489422 0.989484 10.820878 4.077660 0.915330

Antenna 182: 2459990

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 12.706613 12.706613 0.153064 10.183682 -1.281780 11.048026 -0.062419 1.165562 5.246792

Antenna 182: 2459989

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Power inf 246.527131 245.978957 inf inf 2954.900643 2963.635450 4772.964562 4761.498448

Antenna 182: 2459988

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 15.088415 15.088415 0.345567 10.465418 -1.360423 13.261314 -0.700934 0.722414 3.857661

Antenna 182: 2459987

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok ee Temporal Variability 15.496596 0.169927 12.638774 -1.381799 10.345162 15.496596 8.017265 4.431810 2.594379

Antenna 182: 2459986

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 15.499530 15.499530 0.483274 11.158024 -1.105219 11.316802 3.626443 9.886906 2.595480

Antenna 182: 2459985

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 14.017117 14.017117 0.434438 10.400560 -0.872422 8.657785 11.584559 2.287985 10.414465

Antenna 182: 2459984

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 13.486348 0.250117 13.486348 0.263684 10.784678 3.021609 12.121424 -0.904084 3.598452

Antenna 182: 2459983

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 13.174448 0.152347 13.174448 0.093819 10.188555 3.348273 11.211746 0.335167 6.314968

Antenna 182: 2459982

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 10.510283 0.134890 10.510283 -0.629934 8.697161 0.182323 5.315459 0.339387 3.238989

Antenna 182: 2459981

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Temporal Variability 12.422410 12.106894 0.287902 10.829090 -1.153003 12.422410 0.229163 1.130681 7.402290

Antenna 182: 2459980

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 11.695642 11.695642 0.029169 9.907259 -1.155232 10.848173 0.255774 5.352528 0.000658

Antenna 182: 2459979

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 12.170079 0.131346 12.170079 -1.154140 9.257439 -0.326416 10.156395 6.903089 0.769786

Antenna 182: 2459978

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 12.369913 12.369913 0.199564 9.966466 -1.197971 11.023486 -0.050003 1.523037 10.338439

Antenna 182: 2459977

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 13.125412 0.284804 13.125412 -1.109285 9.832856 0.085019 11.364589 6.427282 1.335939

Antenna 182: 2459976

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
182 N13 digital_ok nn Shape 12.606954 12.606954 0.294096 10.234781 -1.147543 10.918255 -0.578666 1.303232 7.012695
In [ ]: